Deciphering the RRM-RNA recognition code: A computational analysis

Joel Roca Martinez, Hrishikesh Balaji Dhondge, Michael Sattler, Wim Vranken

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eucaryotes. Their RNA binding preferences have been investigated for almost two decades, and even though some RRM domains are now very well described, their RNA recognition code has remained elusive. An increasing number of experimental structures of RRM-RNA complexes has become available in recent years. Here, we perform an in-depth computational analysis to derive an RNA recognition code for canonical RRMs. We present and validate a computational scoring method to estimate the binding between an RRM and a single stranded RNA, based on structural data from a carefully curated multiple sequence alignment, which can predict RRM binding RNA sequence motifs based on the RRM protein sequence. Given the importance and prevalence of RRMs in humans and other species, this tool could help design RNA binding motifs with uses in medical or synthetic biology applications, leading towards the de novo design of RRMs with specific RNA recognition.

Original languageEnglish
Article numbere1010859
Number of pages24
JournalPLoS Computational Biology
Issue number1
Publication statusPublished - 23 Jan 2023

Bibliographical note

Publisher Copyright:
© 2023 Roca-Martinez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Copyright 2023 Elsevier B.V., All rights reserved.


  • RRM
  • RNA binding
  • Protein alignment
  • Protein structures
  • prediction


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